Abstract :
[en] The aims of this study were 1) to identify genomic regions associated with a nitrogen (N) efficiency index (NEI) and its composition traits; and 2) to analyze the functional annotation of identified genomic regions. The NEI included N intake (NINT1), milk true protein N (MTPN1), milk urea N yield (MUNY1) in primiparous cattle, N intake (NINT2+), milk true protein N (MTPN2+), and milk urea N yield (MUNY2+) in multiparous cattle (2 to 5 parities). The edited data included 1,043,171 records on 342,847 cows distributed in 1,931 herds. The pedigree consisted of 505,125 animals (17,797 males). Data of 565,049 SNPs were available for 6,998 animals included in the pedigree (5,251 females and 1,747 males). The SNP effects were estimated using a single-step genomic BLUP approach. The proportion of the total additive genetic variance explained by windows of 50 consecutive SNPs (with an average size of about 240 Kb) was calculated. The top-3 genomic regions explaining the largest rate of the total additive genetic variance of the NEI and its composition traits were selected for candidate genes identification and quantitative trait loci (QTL) annotation. The selected genomic regions explained from 0.17% (MTPN2+) to 0.58% (NEI) of the total additive genetic variance. The largest explanatory genomic regions of NEI, NINT1, NINT2+, MTPN1, MTPN2+, MUNY1, MUNY2+ were Bos taurus autosome (BTA) 14 (1.52 – 2.09 Mb), 26 (9.24 – 9.66 Mb), 16 (75.41 – 75.51 Mb), 6 (8.73 – 88.92 Mb), 6 (8.73 – 88.92 Mb), 11 (103.26 – 103.41 Mb), 11 (103.26 – 103.41 Mb). Based on the literature, gene ontology (GO), Kyoto Encyclopedia of Genes and Genomes (KEGG), and protein-protein interaction (PPI), 16 key candidate genes were identified for NEI and its composition traits, which are mainly expressed in the milk cell, mammary, and liver tissues. The number of enriched QTLs related to NEI, NINT1, NINT2+, MTPN1, MTPN2+ were 41, 6, 4, 11, 36, 32, and 32, respectively, and most of them were related to the milk, health, and production classes. In conclusion, this study identified genomic regions associated with NEI and its composition traits, and identified key candidate genes describing the genetic mechanisms of NUE traits. Furthermore, the NEI not only reflects the its composition traits, but also reflects the interaction among them.
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